Search results

This paper aims to improve the refractive index sensor performance for analytes with large refractive index by adopting the technology of microstructured fiber (MF) and surface plasmon resonance (SPR).

The structure adopts an MF with a hexagonal lattice cladding structure composed of all-circular air holes, and three defect regions are introduced. The liquid analyte that needs to be tested is filled in the defect area. The surface plasmon polarition mode is generated and coupled with the core mode, thus forming a refractive index sensing channel. When the resonance conditions are satisfied, the resonance wavelength will be changed with the refractive index of the liquid analyte. All parameters that may affect the performance of the sensor are numerical simulated, and the structure is optimized through a large number of calculations.

The results demonstrate that the maximum dynamic sensitivity (S_R) can reach to 24,260 nm/RIU, and the average sensitivity (S_R-AV) can reach to 18,046 nm/RIU when the refractive index range is from 1.42 to 1.47. Besides, the sensitivity linearity (R²) is approximately 0.965, and its resolution is 4.1 × 10^–6 RIU. The comparison with some literature results shown that the proposed sensor has certain advantages over the sensors reported in these literatures.

This work proposed an SPR-based refractive index sensor with a simple MF structure. It has a certain reference significance for the design and optimization of SPR-based MF sensors. Moreover, owing to its simple structure, high refractive index sensitivity and linear sensing performance, this sensor will play an important role in the detection of high refractive index liquid analytes.

Fierce competition in the crowdfunding market has resulted in high failure rates. Owing to their dedication and efforts, many founders have relaunched failed campaigns as a second attempt. Despite the need for a better understanding, the success of campaign relaunches has not been well-researched. To fill this research gap, this study first theorizes how founders’ learning may enhance their competencies and influence investors’ attribution of entrepreneurial failure. The study then empirically documents the extent and conditions under which such learning efforts impact campaign relaunch performance.

This study examines 5,798 Kickstarter-relaunched campaigns. The founders’ learning efforts are empirically captured by key changes in campaign design that deviate from past business practices. Word movers’ distances and perceptual hashing algorithms (pHash) are used separately to measure differences in campaign textual descriptions and pictorial designs.

Differences in textual descriptions and pictorial designs during campaign failure–relaunch are positively associated with campaign relaunch success. The impacts are further amplified when the previous failures are more severe.

This study is one of the first to examine the success of a campaign relaunch after an initial failure. This study contributes to a better understanding of founders’ learning in crowdfunding contexts and provides insights into the strategies founders can adopt to reap performance benefits.

Achieving accurate trajectory tracking control of robot manipulators is challenging due to dynamic model errors and uncertain payloads. This paper aims to enhance trajectory tracking performance for robots with n degrees of freedom (DOF).

This study proposes a robust motion control framework that combines uncertainty and disturbance estimator with model-based compensation. The proposed framework ensures precise trajectory tracking in robot manipulators. In addition, uncertainties in the high-DOF robot dynamics are estimated through a simple model-based compensation for system error dynamics. The stability of the closed-loop system of the proposed framework is analyzed and proved.

The results indicate that the proposed framework can significantly reduce tracking errors and increase disturbance resistance. The simulation results of a two-link robotic arm verify the effectiveness of the proposed method. The results of the experiments conducted on a seven-DOF torque-controlled Flexiv4S manipulator demonstrate the superior trajectory tracking performance and robustness of the proposed algorithm.

This study introduces a highly efficient, robust motion control framework for high-DOF robots, which can improve the trajectory tracking performance in the presence of model uncertainties.

This study aims to explore the impact of digital supply chain capability (DSCC) on the supply chain financing performance (SCFP) of Chinese small and medium-sized enterprises (SMEs). The mediating role of information sharing (IS) and the moderating role of environmental uncertainty (EU) were also investigated.

Based on information processing theory (IPT), this paper constructs a theoretical model to investigate the impact of DSCC on SCFP in 276 Chinese SMEs using ordinary least regression to test hypotheses.

The results show that both digital supply chain sensing capability (DSC) and digital supply chain responding capability (DRC) have positive effects on SCFP. IS plays a mediating role in the relationship between DSC and SCFP, while the EU strengthens the relationship between DRC and IS.

First, this study takes a capability perspective to explore the impact of DSCC on SCFP, which extends the related studies taking a technology perspective. Second, the inner mechanism between DSCC and SCFP is revealed by introducing IS as a mediator. Third, boundary conditions for the DSCC–IS link are clarified by considering EU as a source of information processing requirements.

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea, wind energy has great potential to become the primary energy. As a critical part of the wind turbine, the gearbox of a wind turbine often bears a large external load. Especially at sea, due to the effects of ocean corrosion, waves and wind, the burden of the wind turbine gearbox is greater, which brings great challenges to its reliability analysis. This study aims to systematically review the reliability research in wind turbine gearboxes and guide future research directions and challenges.

This study systematically reviews some design requirements and reliability analysis methods for wind turbine gearboxes. Then, it summarizes previous studies on wind load uncertainty modeling methods, including the processing of wind measurement data and the summary of three different classifications of random wind speed prediction models. Finally, existing reliability analysis studies on two major parts of the gearbox are described and summarized.

First, the basic knowledge of wind turbine gearboxes and their reliability analysis is introduced. The requirements and reliability analysis methods of wind turbine gearboxes are explained. Then, the processing methods of wind measurement data and three different random wind speed prediction models are described in detail. Furthermore, existing reliability analysis studies on two common parts of wind turbine gearboxes, gears and bearings, are summarized and classified, including a summary of bearing failure modes. Finally, three possible future research directions for wind turbine gearbox reliability analysis are discussed, namely, reliability research under the influence of multiple factors on gears, damage indicators of bearing failure modes and quantitative evaluation criteria for the overall dynamic characteristics of offshore wind turbine gearboxes and a summary is also given.

This paper aims to systematically introduce the relevant contents of wind turbine gearboxes and their reliability analysis. The contents of wind speed data processing, predictive modeling and reliability analysis of major components are also comprehensively reviewed, including the classification and principle introduction of these contents.

The purpose of this study is to investigate the influence of rotational speed on the oil film stability of the hydrostatic rotary table having double rectangular oil pads. The oil film stability is evaluated based on the oil film stiffness under constant load condition and the displacement response amplitude of the oil film under disturbance load condition.

The oil film stability theoretical equations of the double rectangular oil cavity are deduced such as oil film stiffness, damping and dynamic equations. A simulation model is developed to analyze the relationship among oil film temperature, oil film pressure fields and oil film stability. The user-defined function programs are used to control the rotational speed, lubricant viscosity and oil film thickness during the simulation. In addition, an experimental rig is built to test the simulation results.

This study shows that oil film stability decreases with increasing rotational speed under constant load and disturbance load. The trend of oil film stability decreased slowly within 30 r/min, and then rapidly. However, since the hydrodynamic pressure effect, the decrease rate of stability is mitigated under constant load and high rotational speeds.

The conclusions can provide a theoretical basis for improving the oil film stability of machines with similar hydrostatic support structure.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0267/

Given the decisive role of knowledge-oriented leadership (KOL) in boosting organizational innovation capacities, the research intends to investigate the effect of KOL on ambidextrous innovation with the mediating effect of knowledge management capability (KMC). Furthermore, technological turbulence (TT) is regarded as a moderator in the relationship between KMC and ambidextrous innovation.

The data obtained from 122 Pakistani manufacturing firms were used to evaluate the proposed relationships using the partial least square structural equation modeling approach.

The empirical findings demonstrate that KOL positively affects both aspects of ambidextrous innovation, namely exploitative innovation (EII) and exploratory innovation (ERI), with a higher effect on EII. Additionally, knowledge management process capability (KMPC) partially mediates the association between KOL and both dimensions of ambidextrous innovation (EII and ERI). Similarly, knowledge management infrastructure capability (KMIC) mediates the link between KOL and ERI but does not mediate the relationship between KOL and EII. The impacts of the KMPC and KMIC on EII are also significantly moderated by TT, although the link between the two components of the KMC (KMPC and KMIC) and ERI is unaffected.

The research provides useful knowledge and a novel strategy for policymakers to foster KOL and invest in KMC to improve the capabilities of Pakistani manufacturing firms in terms of innovation.

The research has contributed significantly to the resources-based view and knowledge-based view (KBV) literature by examining the various mediation moderation mechanisms and offering greater insights into the relationship between KOL and firms, KMC, and ambidextrous innovations.

Selecting and scheduling optimal project portfolio simultaneously is a complex decision-making problem faced by organizations to realize the strategy. However, dynamic synergy relationships among projects complicate this problem. This study aims at constructing a project portfolio selection and scheduling (PPSS) model while quantifying the dynamic synergetic effects to provide decision support for managing PPSS problems.

This study develops a mathematical model for PPSS with the objective of maximal project portfolio benefits (PPBs). To make the results align with the strategy, comprehensive PPBs are divided into financial and non-financial aspects based on the balanced scorecard. Then, synergy benefits evolve dynamically in the time horizon, and system dynamics is employed to quantify them. Lastly, a case example is conducted to verify the applicability of the proposed model.

The proposed model is an applicable model for PPSS while incorporating dynamic synergy. It can help project managers obtain the results that which project should be selected and when it should start while achieving optimal PPBs.

This study complements prior PPSS research in two aspects. First, financial and non-financial PPBs are designed as new criteria for PPSS, making the results follow the strategy. Second, this study illuminates the dynamic characteristic of synergy and quantifies the synergetic effect. The proposed model provides insights into managing a PPSS effectively.

Research into older adults' use of social media remains limited. Driven by increasing digitalisation in China, the authors focus on Chinese older adults (aged 60–75)’ use of WeChat.

This study used a qualitative interpretive approach and interviewed Chinese older adults to uncover their social practices of WeChat use in everyday life.

By using social practice theory (SPT), the paper unfolds Chinese older adults' social practices of WeChat use in everyday life and reveals how they adopt and resist the drastic changes in Chinese society.

The study contributes to new understandings of SPT from technology use by emphasising the dynamic characteristics of its three elements. The authors synthesise both adoptions and resistance in SPT and highlight the importance of understanding three elements interdependently within specific contexts, which are conditioned by structure and agency.

The purpose of this paper is to conduct a thorough study of the current research status and trends of Artificial Intelligence-Generated Content (AIGC), which is thriving and exerting significant influences on society, the economy and technology. This study will encompass both the ample opportunities and the array of emerging risks and challenges associated with AIGC. Furthermore, this paper seeks to propose practical optimization strategies to facilitate its continued development.

A total of 12,702 documents in Scopus, CNKI and Altmetric.com databases are analyzed in this paper. The visualization tools of CiteSpace and Netdraw are used to systematically analyze AIGC from macro, meso and micro perspectives based on bibliometric indicators. The analysis is combined with altmetrics indicators to identify hotspots in AIGC-related research and predict future development trends. Finally, substantive optimization suggestions for the development of AIGC are put forward.

Research has found that firstly, both domestic and international research in the field of AIGC is actively catching up with the pace of the era. Institutions and authors recognize the indispensability of collaboration, leading to the emergence of interdisciplinary cooperation trends. Secondly, at the thematic research level, both domestic and international studies cover the overall trends of AIGC, including technology, applications, challenges and coping strategies. However, international scholars tend to focus more on technological breakthroughs, while domestic researchers emphasize the formulation of national laws and regulations. Finally, through the analysis of hotspots and trends, it is predicted that future research will focus more on addressing the legal issues regarding the originality of AIGC, enhancing its interactivity, optimizing its applications, emphasizing ethical considerations and efficiently addressing major social issues such as pandemics using AIGC technology. Corresponding optimization strategies are proposed to ensure the development of AIGC is consistent with global consensus and values, creating a beneficial environment for its sustainable development.

Firstly, this paper integrates data from three databases and uses multiple software tools to conduct a comparative analysis of the research trends in AIGC from both domestic and international perspectives. Secondly, this paper not only analyzes the academic influence of AIGC-related research through bibliometric indicators but also combines altmetrics indicators to explore the public’s attitude toward AIGC. This method systematically reveals the overall development trends, leading institutions and researchers, thematic research areas, hotspot evolution and future development trends of AIGC-related research, providing theoretical references for subsequent scholars in AIGC research. Additionally, this paper helps governments, institutions and organizations to precisely and wisely formulate policies and investments, as well as to effectively comprehend the development trends of AIGC and promote the advancement of AIGC technology and applications.